Client Onboarding Forms Processing SOP

graph LR
  A[Google Forms API] --> B[Response Download]
  B --> C[CSV Inventory]
  C --> D[Data Normalization]
  D --> E[Contact Matching]
  E --> F[Gap Analysis]
  F --> G[LACRM Integration]
  G --> H[Completion Tracking]

1 Purpose

Automate collection and processing of client onboarding forms from Google Forms to ensure complete client data capture, accurate contact attribution, and seamless integration with LACRM for client lifecycle management.

2 Triggers

Scheduled: Daily at 4 AM UTC for new form response processing
Manual: Operator execution for immediate onboarding data refresh
Event-driven: New client onboarding, form structure changes, integration issues

3 Inputs

Google Forms API: Direct access to form responses via OAuth integration
CSV Exports: Manual form response exports for backup and validation
Contact Index: Email-to-contact-id mapping for accurate client attribution
LACRM Contact Database: Existing client records for gap analysis and matching

4 Steps

4.1 1. Forms Response Collection

API Integration: Download form responses using Google Forms API with OAuth authentication
Response Metadata: Collect submission timestamps, response IDs, form structure information
CSV Backup: Process manual CSV exports as backup for API integration
Data Validation: Verify response completeness and format consistency

4.2 2. Response Normalization

Column Mapping: Intelligent detection of email, name, and timestamp columns across different forms
Data Standardization: Normalize email formats, name variations, date/time formats
Field Extraction: Extract key onboarding information (contact details, preferences, account types)
Quality Validation: Identify incomplete responses, invalid email formats, missing critical data

4.3 3. Contact Attribution

Email Matching: Map form respondent emails to existing LACRM contact records
Name Verification: Cross-reference respondent names with contact database for accuracy
Fuzzy Matching: Handle email variations, typos, and alternative contact methods
New Contact Detection: Identify responses from individuals not in existing contact database

4.4 4. Onboarding Gap Analysis

Response Coverage: Identify clients with incomplete onboarding form submissions
Missing Forms: Detect expected form responses that haven’t been received
Data Completeness: Analyze response quality and identify missing critical information
Follow-up Generation: Create task lists for incomplete onboarding processes

4.5 5. LACRM Integration

Contact Updates: Enrich existing LACRM records with onboarding form responses
Pipeline Progression: Update client lifecycle status based on form completion
Custom Field Population: Populate LACRM custom fields with form response data
Task Creation: Generate follow-up tasks for incomplete or problematic responses

4.6 6. Completion Tracking

Onboarding Status: Track completion status per client across all required forms
Timeline Analysis: Monitor onboarding duration and identify process bottlenecks
Compliance Verification: Ensure all required documentation and agreements are completed
Reporting: Generate summary reports of onboarding progress and outstanding items

5 Exceptions

5.1 Form Response Issues

Incomplete Responses: Handle partial form submissions and missing required fields
Invalid Data: Process responses with malformed emails or invalid input data
Duplicate Submissions: Identify and handle multiple submissions from same individual
Spam Responses: Filter out automated or fraudulent form submissions

5.2 Contact Matching Failures

Unmatched Emails: Responses from email addresses not in contact database
Multiple Matches: Single email associated with multiple LACRM contacts
Name Conflicts: Response names don’t match associated contact records
Resolution: Flag for manual review and contact database maintenance

5.3 Integration Issues

Google Forms API: Authentication failures or API quota limitations
LACRM Updates: API failures during contact enrichment or field updates
Data Quality: Validation failures or schema mismatches between systems
Recovery: Automatic retry with exponential backoff, manual escalation procedures

5.4 Processing Errors

CSV Format Issues: Malformed or inconsistent CSV export formats
Encoding Problems: Character encoding issues in international responses
File Access: Missing or corrupted form export files
Performance: Processing timeouts for large response datasets

6 Owner Handoffs

Client Experience → Data Engineering for contact resolution and matching issues
Client Experience → Compliance for incomplete documentation or regulatory requirements
Data Engineering → Client Experience for new contact creation and assignment decisions

7 SLAs

Daily Processing: Complete within 60 minutes of 4 AM UTC start time
Manual Processing: Complete within 30 minutes for urgent onboarding needs
Error Resolution: Automatic retry within 15 minutes, manual escalation at 2 hours
Data Currency: Form responses processed within 24 hours of submission

8 Controls

PII Protection: Secure handling of personal information in form responses
Data Validation: Email format verification, required field completeness checks
Contact Attribution: Accurate mapping of responses to correct client records
Quality Assurance: Validation of processed data before LACRM integration

9 Audit Artifacts

Processing Logs: Detailed execution logs with response counts and error information
Match Reports: Contact attribution success rates and unmatched response analysis
Quality Reports: Data completeness analysis and validation failure summaries
Completion Tracking: Onboarding progress reports and outstanding task summaries

10 Data Processing Workflow

10.1 Raw Data Collection

Form Structure Analysis: Dynamic detection of form fields and question types
Response Extraction: Raw response data with metadata preservation
CSV Inventory: Catalog of available form exports with processing status

10.2 Normalization Pipeline

Column Detection: Intelligent mapping of form fields to standard data schema
Email Standardization: Lowercase conversion, whitespace trimming, format validation
Name Processing: First/last name extraction, format standardization, duplicate handling

10.3 Matching Algorithm

Exact Email Match: Primary matching method using normalized email addresses
Name Cross-Reference: Secondary validation using contact name information
Confidence Scoring: Attribution confidence levels for quality assessment

11 Business Impact

Onboarding Efficiency: Automated processing reduces manual data entry and errors
Client Experience: Faster onboarding progression and reduced follow-up needs
Compliance Tracking: Complete visibility into documentation completion status
Data Quality: Consistent client information across all systems and touchpoints

12 Monitoring & Alerts

Processing Success: Form response counts, contact matches, integration updates
Quality Metrics: Attribution accuracy, data completeness, validation success rates
Error Conditions: API failures, matching problems, data quality issues
Business KPIs: Onboarding completion rates, average processing time, client satisfaction

13 FAQs

How are multiple responses from the same client handled? The system processes all responses but identifies duplicates based on email address. The most recent complete response takes precedence, with earlier responses archived for reference.

What happens when form responses contain new contact information? New contacts are flagged for manual review and potential addition to LACRM. The system doesn’t automatically create contacts to prevent database pollution.

How are form structure changes handled? The normalization pipeline uses intelligent column detection to adapt to form changes. Significant structural changes may require manual configuration updates.

Can the system process forms in languages other than English? Yes, the system handles UTF-8 encoding and international characters. However, contact matching relies on email addresses which are typically ASCII-based.